Title :
Traffic sign recognition in color image sequences
Author_Institution :
Res. Center Ulm, Daimler Benz AG, Germany
fDate :
29 Jun-1 Jul 1992
Abstract :
At the Daimler-Benz Research Center in Ulm a system for traffic sign recognition is under development. The task of the system is to detect and interpret traffic signs in colour image sequences; these images are acquired by a camera mounted in a car. The color segmentation of the incoming images is performed with a high order neural network. Based on this color segmented images and using a priori knowledge, hypotheses on image regions containing traffic signs are generated. The kind of traffic sign is also hypothesized. The preselected image regions are further analysed in order to verify or reject the hypothesis. The analysis finally interprets the contents of the traffic signs. The control of the analysis is supported by knowledge on traffic signs and outdoor scenes in general. The whole knowledge is stored in a framebased network
Keywords :
automobiles; computer vision; image recognition; image segmentation; image sequences; knowledge based systems; neural nets; Daimler-Benz Research Center; automobiles; color image sequences; color segmentation; computer vision; framebased network; image recognition; knowledge based systems; neural network; traffic sign recognition; Cameras; Color; Communication system traffic control; Image analysis; Image recognition; Image segmentation; Image sequences; Layout; Neural networks; Telecommunication traffic;
Conference_Titel :
Intelligent Vehicles '92 Symposium., Proceedings of the
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-0747-X
DOI :
10.1109/IVS.1992.252226
